Larsen, S. S.

Weisz, D. R.

Charlton, J. C.

Abstract [en]

We present the Snapshot Hubble U-band Cluster Survey (SHUCS), a project aimed at characterizing the star cluster populations of 10 nearby galaxies (d < 23 Mpc, half within approximate to 12 Mpc) through new F336W (U-band equivalent) imaging from Wide Field Camera 3, and archival BVI-equivalent data with the Hubble Space Telescope. Completing the UBVI baseline reduces the age-extinction degeneracy of optical colors, thus enabling the measurement of reliable ages and masses for the thousands of clusters covered by our survey. The sample consists chiefly of face-on spiral galaxies at low inclination, in various degrees of isolation (isolated, in group, merging), and includes two active galactic nucleus hosts. This first paper outlines the survey itself, the observational datasets, the analysis methods, and presents a proof-of-concept study of the large-scale properties and star cluster population of NGC 4041, a massive SAbc galaxy at a distance of approximate to 23 Mpc, and part of a small grouping of six giant members. We resolve two structural components with distinct stellar populations, a morphology more akin to merging and interacting systems. We also find strong evidence of a truncated, Schechter-type mass function, and a similarly segmented luminosity function. These results indicate that binning must erase much of the substructure present in the mass and luminosity functions, and might account for the conflicting reports on the intrinsic shape of these functions in the literature. We also note a tidal feature in the outskirts of the galaxy in Galaxy Evolution Explorer UV imaging, and follow it up with a comprehensive multi-wavelength study of NGC 4041 and its parent group. We deduce a minor merger as a likely cause of its segmented structure and the observed pattern of a radially decreasing star formation rate. We propose that combining the study of star cluster populations with broadband metrics is not only advantageous, but often easily achievable thorough archival datasets.